Clustering of Social and Physical Pain Variables and Their Association With Mortality in Two Population-Based Cohorts

Social pain and physical pain are related bidirectionally, but how these variables cluster in the population is unknown.

This study included 2833 women from the Study of Women's Health Across the Nation (SWAN), a community-based cohort of middle-aged women, and 3972 women from the Pathways Study, a population-based cohort of women diagnosed with American Joint Committee on Cancer stages I-IV breast cancer diagnosed between 2005 and 2013. Women provided data on measures related to social pain (social network size, social support, loneliness, social well-being) and physical pain (sensitivity to pain, bodily pain) at study baseline. Analyzing each cohort separately, we used latent class analysis to evaluate social-physical pain clusters, logistic regression to evaluate predictors of categorization into clusters, and Cox proportional hazards models to evaluate associations of clusters with all-cause mortality. We also performed a meta-analysis to combine cohort mortality associations.

Each cluster analysis produced a "low social-physical pain" cluster (SWAN, 48.6%; Pathways, 35.2%) characterized by low social and pain symptoms, a "high social-physical pain" cluster (SWAN, 17.9%; Pathways, 17.9%) characterized by high symptoms, and a "low social/high physical pain" cluster of women with high pain and compromised social functioning but otherwise low social symptoms (SWAN, 33.5%; Pathways, 46.9%). In meta-analysis, categorization into the high social-physical pain cluster was associated with elevated mortality (adjusted hazard ratio = 1.34, 95% confidence interval = 1.05-1.71, Q statistic = 0.782), compared with those in the low social-physical pain cluster.

In two cohorts of women, latent class analysis produced similar sets of social-physical pain clusters, with the same proportion having both high social and pain symptoms; women in this cluster had elevated mortality.